knitr::opts_chunk$set(fig.width = 8, collapse = TRUE)

knitr::opts_chunk$set(engine.path = list(
                      python = 'C:/Users/Stefan/AppData/Local/Programs/Python/Python36/python',
                      stata = 'C:/git/stata15/StataSE.exe')

num = 8 
num_sqrt = num ** 0.5
print('The square root of %0.3f is %0.3f'%(num ,num_sqrt))

library(Statamarkdown)
# stataexe <- find_stata()
knitr::opts_chunk$set(engine.path=list(stata="C:/git/stata15/StataSE.exe"),
  error=TRUE, cleanlog=TRUE, comment=NA)

sysuse auto, clear
generate gpm = 1/mpg
summarize price gpm

data <- read.csv("C:/Users/Stefan/Documents/IPSD/data_vis/week_3/footballdata.csv" ,
                 header=TRUE, sep=",", encoding = "UTF-8")

data_filtered <- data %>%
    group_by(Position, League) %>%
    summarise(avg_attack = round(mean(Attack, na.rm = T), 2)) %>%
    filter(!is.na(Position))

knitr::kable(data_filtered) %>%
       kable_styling("striped", full_width = F) %>%
       column_spec(2, bold = T) %>%
       pack_rows("Verteidiger", 1, 4, 
            label_row_css = "background-color: #666; color: #fff;") %>%
       pack_rows("Stürmer", 5, 8, 
            label_row_css = "background-color: #666; color: #fff;") %>%
       pack_rows("Torhüter", 9, 12, 
            label_row_css = "background-color: #666; color: #fff;") %>%
       pack_rows("Mittelfeld", 13, 16, 
            label_row_css = "background-color: #666; color: #fff;") %>%
       row_spec(c(1,8,11,14), bold = T, color = "white", background = "green")

data_filtered %>%
    mutate_if(is.numeric, function(x) {
    cell_spec(x, bold = T,
    color = spec_color(x, end = 0.9),
    font_size = spec_font_size(x))}) %>%

    mutate(League = cell_spec(League, color = "white", 
                              bold = T, 
                              background = spec_color(1:4, end = 0.9, option = "A", 
                                                      direction = -1))) %>%
  
    kable(escape = F, align = "c") %>%
    kable_styling(c("striped", "condensed"), full_width = F)

# install.packages('DT')
datatable(data_filtered)

N <- 1000
N1 <- 123
nh <- 66
f <- 8/N1
stratum1_variance <- 33.453

# $$var_{(\bar{y}_{w})_{1}}  = (`r N1`/`r N`)^2 * (1-(`r f`))/`r nh` * `r stratum1_variance`$$
# $$var_{(\bar{y}_{w})_{1}}  = `r (N1/N)^2` * `r (1-(f))/nh * stratum1_variance`$$
# $$var_{(\bar{y}_{w})_{1}}  = `r (N1/N)^2 * (1-(f))/nh * stratum1_variance`$$

# bullet
data_filtered <- data %>%
  filter(Position == "Goalkeeper")

data_filtered <- subset(data_filtered, select=c(Name, KeeperSkills))

fig <- plot_ly() 
fig <- fig %>%
  add_trace(
    type = "indicator",
    mode = "number+gauge+delta",
    value = data_filtered[34,2],
    delta = list(reference = 85),
    domain = list(x = c(0.25, 1), y = c(0.1, 0.3)),
    title =list(text = paste0(data_filtered[34,1])),
    gauge = list(
      shape = "bullet",
      axis = list(range = c(0, 100)),
      threshold = list(
        line= list(color = "black", width = 2),
        thickness = 0.75,
        value = 85),
      steps = list(
        list(range = c(0, 50), color = "#fc9272"),
        list(range = c(50, 80), color = "#ffeda0"),
        list(range = c(80, 100), color = "#a1d99b")),
      bar = list(color = "black")))
fig <- fig %>%
  add_trace(
    type = "indicator",
    mode = "number+gauge+delta",
    value = data_filtered[19,2],
    delta = list(reference = 85),
    domain = list(x = c(0.25, 1), y = c(0.4, 0.6)),
    title =list(text = paste0(data_filtered[19,1])),
    gauge = list(
      shape = "bullet",
      axis = list(range = c(0, 100)),
      threshold = list(
        line= list(color = "black", width = 2),
        thickness = 0.75,
        value = 85),
      steps = list(
        list(range = c(0, 50), color = "#fc9272"),
        list(range = c(50, 80), color = "#ffeda0"),
        list(range = c(80, 100), color = "#a1d99b")),
      bar = list(color = "black"))) 
fig <- fig %>%
  add_trace(
    type = "indicator",
    mode = "number+gauge+delta",
    value = data_filtered[173,2],
    delta = list(reference = 85),
    domain = list(x = c(0.25, 1), y = c(0.7, 0.9)),
    title =list(text = paste0(data_filtered[173,1])),
    gauge = list(
      shape = "bullet",
      axis = list(range = c(0, 100)),
      threshold = list(
        line= list(color = "black", width = 2),
        thickness = 0.75,
        value = 85),
      steps = list(
        list(range = c(0, 50), color = "#fc9272"),
        list(range = c(50, 80), color = "#ffeda0"),
        list(range = c(80, 100), color = "#a1d99b")),
      bar = list(color = "black"))) 
fig

data_filtered <- data %>%
  group_by(Position, League) %>%
  filter(Position != "Goalkeeper") %>%
  summarise(avg_attack = mean(DribbleSpeed, na.rm = T)) %>%
  filter(!is.na(Position))

DribbleSpeed <- ggplotly(ggplot() +
  geom_line(aes(League, avg_attack, colour = Position, group = Position),
            data = data_filtered, size=2) +
  theme_bw() +
  theme(axis.title.x=element_blank(),
        axis.title.y=element_blank())+
  ylim(70,100)+
  labs(x = "League", y = "Mean DribbleSpeed Score", color = "Position",
       title = "Average DribbleSpeed Score by League and Position",
       caption = "Data: footballdata"))

DribbleSpeed

rmarkdown::render("C:/git/gitHub/rmarkdown_praesentation/output/league_report.Rmd", 
                  output_file = "C:/git/gitHub/rmarkdown_praesentation/output/LaLiga_report.pdf",
                  params = list(nms = "LaLiga"))

library(purrr)

render_report <- function(path, league) {
  rmarkdown::render(
    path,
    params = list(nms = league),
    output_file = paste0("C:/git/gitHub/rmarkdown_praesentation/output/", 
                         league, "_report.pdf")
  )
}

map(c("Bundesliga", "PremierLeague", "LaLiga", "SerieA"),
    render_report,
    path = "C:/git/gitHub/rmarkdown_praesentation/output/league_report.Rmd")